code: def test_wrong_inputs():
      with pytest.raises(
          ValueError,
          match=r"Argument num_features must be greater to zero",
      ):
          FID(num_features=-1, feature_extractor=torch.nn.Identity())
  
      with pytest.raises(
          ValueError,
          match=r"feature_extractor output must be a tensor of dim 2, got: 1",
      ):
          FID(
              num_features=1, feature_extractor=torch.nn.Identity()
          ).update(torch.tensor([[], []]))
  
      with pytest.raises(
          ValueError,
          match=r"Batch size should be greater than one, got: 0",
      ):
          FID(
              num_features=1, feature_extractor=torch.nn.Identity()
          ).update(torch.rand(2, 0, 0))
  
      with pytest.raises(
          ValueError,
          match=r"num_features returned by feature_extractor should be 1, got: 0",
      ):
          FID(
              num_features=1, feature_extractor=torch.nn.Identity()
          ).update(torch.rand(2, 2, 0))
  
      err_str = "Number of Training Features and Testing Features should be equal (torch.Size([9, 2]) != torch.Size([5, 2]))"
      with pytest.raises(ValueError, match=re.escape(err_str)):
          FID(
              num_features=2, feature_extractor=torch.nn.Identity()
          ).update((torch.rand(9, 2), torch.rand(5, 2)))
  
      with pytest.raises(
          TypeError,
          match=r"Argument feature_extractor must be of type torch.nn.Module",
      ):
          FID(num_features=1, feature_extractor=lambda x: x)
  
      with pytest.raises(
          ValueError,
          match=r"Argument num_features must be provided, if feature_extractor is specified.",
      ):
          FID(feature_extractor=torch.nn.Identity())
  
imports: import os
  import re
  from unittest.mock import patch
  import pytest
  import pytorch_fid.fid_score
  import scipy
  import torch
  from numpy import cov
  import ignite.distributed
  from ignite.metrics.gan.fid import FID, fid_score
label_desc: Use image node_id 9 for calling a global function with example usage: test_wrong_inputs() without return types